A systematic review on deep-learning-based phishing email detection

K Thakur, ML Ali, MA Obaidat, A Kamruzzaman - Electronics, 2023 - mdpi.com
Phishing attacks are a growing concern for individuals and organizations alike, with the
potential to cause significant financial and reputational damage. Traditional methods for …

Across the Spectrum In-Depth Review AI-Based Models for Phishing Detection

S Ahmad, M Zaman, AS AL-Shamayleh… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
Advancement of the Internet has increased security risks associated with data protection and
online shopping. Several techniques compromise Internet security, including hacking, SQL …

[HTML][HTML] Enhanced feature selection using genetic algorithm for machine-learning-based phishing URL detection

E Kocyigit, M Korkmaz, OK Sahingoz, B Diri - Applied sciences, 2024 - mdpi.com
In recent years, the importance of computer security has increased due to the rapid
advancement of digital technology, widespread Internet use, and increased sophistication of …

[PDF][PDF] Real-time phishing detection using deep learning methods by extensions

DM Linh, HD Hung, HM Chau, QS Vu… - International Journal of …, 2024 - researchgate.net
Phishing is an attack method that relies on a user's insufficient vigilance and understanding
of the internet. For example, an attacker creates an online transaction website and tricks …

A Two-Stage Hybrid Approach for Phishing Attack Detection Using URL and Content Analysis in IoT

SY Mohammed, M Aljanabi, MM Mijwil… - BIO Web of …, 2024 - bio-conferences.org
The goal of phishing assaults is to trick users into giving up personal information by making
them believe they need to act quickly on critical information. The creation of efficient …

Intrusion Detection with deep learning: A literature review

BK Sedraoui, A Benmachiche… - … on Pattern Analysis …, 2024 - ieeexplore.ieee.org
As technology continues to grow and becomes increasingly integral to education, institutions
and universities worldwide are making substantial investments in e-learning platforms to …

Advancement of Phishing Attack Detection Using Machine Learning

K Elumalai, D Bose - Journal of Electrical Systems, 2024 - search.proquest.com
Phishing attacks continue to pose significant threats to individuals and organizations,
necessitating the development of advanced detection mechanisms. This study, propose a …

PhishGuard: A Convolutional Neural Network Based Model for Detecting Phishing URLs with Explainability Analysis

MR Islam, MM Islam, M Afrin, A Antara… - arXiv preprint arXiv …, 2024 - arxiv.org
Cybersecurity is one of the global issues because of the extensive dependence on cyber
systems of individuals, industries, and organizations. Among the cyber attacks, phishing is …

Optimizing Phishing Detection Systems with Ensemble Learning: Insights from a Multi-Model Voting Classifier

P Singh, T Hasija, K Ramkumar - 2024 5th International …, 2024 - ieeexplore.ieee.org
Phishing attempts threaten cybersecurity, hence strong detection systems are necessary.
This research study highlights the utilization of ensemble learning methods to improve …

Integrated Machine Learning Approach to Phishing Detection: Comparing SVM, Random Forest, and XGBoost Models

P Singh, T Hasija, KR Ramkumar - 2024 4th International …, 2024 - ieeexplore.ieee.org
The objective of this research is to create a phishing detection system that is both efficient
and effective. This system will be based on sophisticated machine learning models …